| 研究実績の概要 |
In this project, we study mobile data offloading problem from both from network side perspective and mobile users’ perspective.
For the second year, we study the mobile users' offloading policy to minimize his monetary cost and energy consumption with unknown mobile user mobility pattern. We propose to use a kind of reinforcement learning technique called deep Q-network (DQN) for mobile user to learn the optimal offloading policy from past experiences. Extensive simulations are conducted to validate our proposed offloading algorithms.
We have published two journal papers and several international conference papers like International Conference on Network and Service Management and domestic conferences papers.
|
